
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))


# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "54"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder


# Use environment variables to figure out path to the csvs and auto_metrics
antenna = os.environ["ANTENNA"]
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "24"
csv_folder = "/home/obs/src/H5C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H5C_Notebooks/auto_metrics_inspect"


display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))


import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna


# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, '*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 134 csvs in /home/obs/src/H5C_Notebooks/_rtp_summary_
Found 129 auto_metrics notebooks in /home/obs/src/H5C_Notebooks/auto_metrics_inspect


# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'


this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        antnum = row['Ant']
        if antnum != int(antenna):
            continue
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break


# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])


display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))


html_to_display = ''
for am_html in auto_metric_htmls:
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line: 
            break


HTML(html_to_display)

JDs	A Priori Status	Auto Metrics Flags	Dead Fraction in Ant Metrics (Jee)	Dead Fraction in Ant Metrics (Jnn)	Crossed Fraction in Ant Metrics	Flag Fraction Before Redcal	Flagged By Redcal chi^2 Fraction	ee Shape Modified Z-Score	nn Shape Modified Z-Score	ee Power Modified Z-Score	nn Power Modified Z-Score	ee Temporal Variability Modified Z-Score	nn Temporal Variability Modified Z-Score	ee Temporal Discontinuties Modified Z-Score	nn Temporal Discontinuties Modified Z-Score	Average Dead Ant Metric (Jee)	Average Dead Ant Metric (Jnn)	Average Crossed Ant Metric	Median chi^2 Per Antenna (Jee)	Median chi^2 Per Antenna (Jnn)
2459594	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	98.424439	69.560720	180.361639	139.676101	34.701723	32.908828	104.783537	89.418016	0.0168	0.0171	0.0011	1.136315	1.148012
2459593	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	94.489896	92.632537	180.326339	183.528316	58.473936	80.169011	202.628018	233.718908	0.0170	0.0166	0.0006	1.101191	1.097465
2459592	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	7.228530	11.623212	115.656526	57.613014	254.450998	48.843715	306.846545	60.846630	0.0162	0.0170	0.0008	nan	nan
2459591	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	267.947044	113.804277	306.070558	210.222980	94.872022	62.323925	786.093401	269.159244	0.0163	0.0165	0.0003	1.092750	1.102342
2459590	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	324.855462	182.556505	256.764339	200.116185	41.421626	41.187839	250.369354	278.659082	0.0163	0.0164	0.0004	1.124148	1.129536
2459589	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	337.054727	337.489416	inf	inf	45.778678	49.773900	343.883121	363.299255	nan	nan	nan	0.000000	0.000000
2459588	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	178.870043	81.325083	277.406898	207.417489	36.531113	29.367972	52.716845	56.044446	0.0163	0.0167	0.0005	1.087501	1.096994
2459587	RF_maintenance	100.00%	-	-	-	100.00%	0.00%	326.440818	93.706473	465.726910	273.661354	114.366300	45.382743	721.379261	349.771576	nan	nan	nan	0.000000	0.000000
2459586	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	133.155444	128.800005	65.609225	61.247056	20.817838	21.836611	470.442946	294.535855	0.0172	0.0167	0.0011	1.119126	1.123617
2459585	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	81.415077	52.750434	54.204367	38.559421	10.361829	12.319049	896.082773	521.356455	0.0172	0.0166	0.0005	0.000000	0.000000
2459584	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	73.278102	127.683050	242.576550	235.184227	25.015936	23.558561	130.272191	118.809844	0.0170	0.0165	0.0006	0.000000	0.000000
2459583	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	104.494032	90.407660	120.888238	73.314624	126.530183	26.993287	804.531084	214.144334	0.0166	0.0171	0.0005	1.126258	1.133110
2459582	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	46.631604	72.669672	74.399198	59.789772	70.312513	30.737096	394.159741	144.656903	0.0169	0.0170	0.0010	1.075243	1.086880
2459581	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	55.719394	102.641964	76.075654	77.856103	44.437928	30.725795	288.454087	280.210980	0.0175	0.0164	0.0009	1.103104	1.100408
2459580	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	77.757013	91.271154	104.460305	88.276410	72.887976	43.236752	557.968100	349.997370	0.0165	0.0162	0.0004	1.114525	1.116793
2459579	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	63.217158	75.914820	114.715270	86.779776	78.873650	35.389880	937.729338	407.113612	0.0164	0.0165	0.0004	1.043027	1.049292
2459578	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	6.869406	11.953534	36.770944	31.528142	230.448886	132.421131	1106.759052	780.090522	0.0167	0.0164	0.0004	nan	nan
2459577	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	67.481461	100.044105	84.846939	70.407278	53.142205	41.005594	372.453096	253.933902	0.0164	0.0166	0.0004	1.105039	1.110637
2459576	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	69.431820	120.894303	68.546677	69.908465	66.722267	52.391017	560.747381	442.459606	0.0166	0.0161	0.0006	1.009870	1.010378
2459575	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	49.738036	78.739517	74.891981	56.090686	52.278508	17.140329	84.576991	34.822320	0.0168	0.0167	0.0005	0.000000	0.000000
2459574	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	69.079739	78.578150	69.221021	57.212161	58.005980	53.043585	368.305005	239.085131	0.0164	0.0165	0.0003	1.076987	1.081183
2459573	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	76.941118	81.515060	123.273838	97.695450	92.783456	47.387578	737.276995	460.249666	0.0167	0.0165	0.0004	0.000000	0.000000
2459572	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	51.371672	87.049360	62.012578	52.008788	34.064547	22.877364	787.120776	495.165179	0.0163	0.0167	0.0004	0.753049	0.753108
2459571	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	6.308673	10.581147	41.937554	35.671520	215.163837	143.511742	1304.509369	977.561317	0.0164	0.0164	0.0003	nan	nan
2459570	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459569	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	67.148683	77.373704	86.591253	66.552150	35.548186	16.949517	58.483072	29.638085	0.0162	0.0166	0.0005	0.945681	0.954087
2459566	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	32.437311	78.828562	63.700238	65.759031	22.802524	34.783641	131.735850	136.161671	0.0176	0.0167	0.0008	1.031764	1.030774
2459565	RF_maintenance	0.00%	-	-	-	100.00%	0.00%	-1.318369	-1.318369	-1.270881	-1.270881	-0.651706	-0.651706	-0.774639	-0.774639	nan	nan	nan	0.000000	0.000000
2459564	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	69.272253	94.797799	91.121081	78.431825	18.710436	11.401110	428.742662	199.272537	0.0163	0.0164	0.0004	1.084454	1.088140
2459563	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	47.439716	97.832947	151.080107	140.072193	50.997838	39.472707	441.704849	254.029914	0.0165	0.0165	0.0003	0.000000	0.000000
2459562	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	35.352345	66.991571	37.699907	41.532375	15.977194	11.605391	259.842865	242.746989	0.0165	0.0162	0.0004	1.110735	1.108536
2459561	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	65.445443	82.477534	48.837429	40.011580	22.488918	9.289574	720.696661	380.839871	0.0162	0.0163	0.0003	1.115064	1.119610
2459560	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	50.528195	63.046159	43.710351	34.248750	17.595308	10.418062	416.112015	238.877559	0.0164	0.0165	0.0005	1.114432	1.121716
2459559	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	44.366689	84.217052	43.193472	37.141838	11.807868	7.453459	395.376079	180.211371	0.0167	0.0165	0.0007	1.092036	1.097226
2459558	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	54.130276	100.494792	83.128955	82.600958	51.259374	34.373735	518.111101	371.695278	0.0168	0.0163	0.0004	1.094768	1.096274
2459557	RF_maintenance	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0163	0.0165	0.0002	nan	nan
2459556	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	51.411417	94.236799	86.716307	87.888553	47.008761	44.908126	996.714227	929.977640	0.0165	0.0164	0.0004	1.093541	1.093202
2459554	RF_maintenance	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0166	0.0166	0.0004	nan	nan
2459553	RF_maintenance	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0163	0.0164	0.0004	nan	nan
2459552	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	50.386695	125.305394	108.346659	118.362722	45.836517	67.538161	315.863449	414.187460	0.0169	0.0162	0.0005	0.000000	0.000000
2459551	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	27.328487	56.108589	40.064681	40.649856	11.541547	8.665609	252.657828	237.565719	0.0171	0.0165	0.0005	1.100036	1.101328
2459550	RF_maintenance	-	96.71%	96.71%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0326	0.0325	0.0003	nan	nan
2459549	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	97.319790	84.301930	123.533040	85.727361	109.310737	49.898752	1253.837508	523.903232	0.0163	0.0165	0.0004	1.088616	1.096400
2459542	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	86.426163	124.725452	231.731139	177.422872	13.006269	5.474536	967.508163	301.750941	0.0164	0.0163	0.0005	1.112459	1.116389
2459541	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	10.805824	11.020404	46.484980	46.969723	698.282447	685.597984	24.930368	29.097447	0.0168	0.0166	0.0004	1.028104	1.029250
2459540	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	34.569732	90.086925	34.422847	41.584834	15.887676	26.721311	123.611055	229.007421	0.0172	0.0162	0.0006	1.114479	1.106659
2459536	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	81.115554	129.863896	142.546396	144.788374	89.539911	68.370801	884.685767	764.259235	0.0166	0.0163	0.0003	1.132791	1.131451
2459535	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	28.741412	75.422608	32.366276	36.965014	22.759903	29.403129	186.898788	238.044509	0.0171	0.0163	0.0006	1.089803	1.093078
2459534	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	43.586533	59.701849	38.405757	32.258833	29.260734	22.435433	287.865069	150.907408	0.0163	0.0166	0.0003	1.110050	1.118459
2459533	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	128.039267	115.522470	118.249842	85.974319	93.763530	52.231760	1170.426224	439.406608	0.0161	0.0162	0.0003	1.120614	1.124056
2459532	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	64.016048	123.723206	107.891820	123.911929	60.675393	127.226133	445.057828	673.027726	0.0168	0.0162	0.0005	1.113657	1.111580
2459530	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	44.100032	74.825790	37.071452	33.256948	33.047560	11.920112	405.848533	202.281674	0.0163	0.0165	0.0003	1.078187	1.083474
2459527	RF_maintenance	0.00%	-	-	-	100.00%	0.00%	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459524	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	48.073014	108.908095	119.388974	129.774257	142.384532	181.184325	333.042364	430.877686	0.0168	0.0161	0.0005	0.000000	0.000000
2459523	RF_maintenance	100.00%	-	-	-	100.00%	0.00%	113.028458	133.602788	154.036705	106.743593	101.507133	48.722393	1030.191200	290.253721	nan	nan	nan	1.393985	1.397309
2459522	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	47.109664	98.947637	104.396205	130.939333	90.543316	202.012444	397.684619	978.541711	0.0169	0.0162	0.0005	1.115200	1.114281
2459513	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	7.972699	17.276109	38.819657	56.906122	350.400394	517.878596	1261.836366	2474.374659	0.0172	0.0161	0.0009	nan	nan
2459508	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	55.278357	111.824873	112.892806	105.175313	77.994347	40.949352	108.121066	72.300610	0.0167	0.0166	0.0004	0.000000	0.000000
2459505	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	60.693874	104.480559	101.464691	103.357819	70.682556	126.221255	452.713477	532.109394	0.0079	0.0070	0.0016	1.136660	1.128519
2459503	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	43.965621	136.816953	142.718049	219.967892	57.350832	113.543358	245.125303	1230.045139	0.0088	0.0058	0.0074	0.000000	0.000000

Antenna Season Report Notebook¶

Antenna 24 Report

Load relevant info from summary CSVs¶

Table 1: Per-Night RTP Summary Info For This Atenna¶

Antenna 24, Node 0:

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

Antenna 24: 2459661

Antenna 24: 2459660

Antenna 24: 2459659

Antenna 24: 2459658

Antenna 24: 2459657

Antenna 24: 2459656

Antenna 24: 2459655

Antenna 24: 2459653

Antenna 24: 2459652

Antenna 24: 2459651

Antenna 24: 2459650

Antenna 24: 2459649

Antenna 24: 2459648

Antenna 24: 2459647

Antenna 24: 2459646

Antenna 24: 2459645

Antenna 24: 2459642

Antenna 24: 2459640

Antenna 24: 2459639

Antenna 24: 2459638

Antenna 24: 2459637

Antenna 24: 2459636

Antenna 24: 2459635

Antenna 24: 2459634

Antenna 24: 2459633

Antenna 24: 2459632

Antenna 24: 2459631

Antenna 24: 2459630

Antenna 24: 2459629

Antenna 24: 2459628

Antenna 24: 2459627

Antenna 24: 2459626

Antenna 24: 2459625

Antenna 24: 2459624

Antenna 24: 2459623

Antenna 24: 2459622

Antenna 24: 2459621

Antenna 24: 2459620

Antenna 24: 2459619

Antenna 24: 2459618

Antenna 24: 2459617

Antenna 24: 2459616

Antenna 24: 2459615

Antenna 24: 2459614

Antenna 24: 2459613

Antenna 24: 2459612

Antenna 24: 2459611

Antenna 24: 2459610

Antenna 24: 2459609

Antenna 24: 2459608

Antenna 24: 2459607

Antenna 24: 2459605

Antenna 24: 2459604

Antenna 24: 2459603

Antenna 24: 2459602

Antenna 24: 2459598

Antenna 24: 2459597

Antenna 24: 2459596

Antenna 24: 2459595

Antenna 24: 2459594

Antenna 24: 2459593

Antenna 24: 2459592

Antenna 24: 2459591

Antenna 24: 2459590

Antenna 24: 2459589

Antenna 24: 2459588

Antenna 24: 2459587

Antenna 24: 2459586

Antenna 24: 2459585

Antenna 24: 2459584

Antenna 24: 2459583

Antenna 24: 2459582

Antenna 24: 2459581

Load antenna metric spectra and waterfalls from `auto_metrics` notebooks.¶